通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026
通用机器学习:unsupervised_and_semisupervised_learning
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 2,683 篇被归入该主题的论文。
主要结论
- 通用机器学习 · unsupervised and semisupervised learning论文从 2023 年的 649 篇增长到 2026 年的 799 篇,三年间扩大到约 1.2 倍。
- ICML 是发通用机器学习 · unsupervised and semisupervised learning论文最多的会议,2023–2026 年共 859 篇,占四个会议总量的 32%。
- 交叉方向里涨得最快的是深度学习 · self supervised learning:同时属于两个主题的论文从 2023 年的 23 篇增至 2026 年的 86 篇。
- 在「通用机器学习」的 6 个主题里,它的 2026 年论文数排第 1;同组增长最快的通用机器学习 · evaluation是 4.3 倍,通用机器学习 · unsupervised and semisupervised learning是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
代表论文
按年份和会议均匀挑选,方便快速看到每一届的样貌
- NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
- ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
- ICLR 2026A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data
- CVPR 2026COG Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object
- NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
- ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
- ICLR 2025A General Framework for Producing Interpretable Semantic Text Embeddings
- CVPR 2025A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening
- NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
- ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
- ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
- CVPR 2024Dual Prototype Attention for Unsupervised Video Object Segmentation
- NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
- ICML 2023A Mathematical Model for Curriculum Learning for Parities
- ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
- CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
- NeurIPS 2026Attention-based PCA
- ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
- ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
- CVPR 2026CROWn A Unified Framework for Anti-Aliased Downsampling and Phase-Calibrated Fusion
全部通用机器学习 · unsupervised and semisupervised learning论文
共 798 篇,第 3 / 16 页
- ICLR 2026Context and Diversity Matter: The Emergence of In-Context Learning in World Models
- ICLR 2026Contrastive Predictive Coding Done Right for Mutual Information Estimation
- ICLR 2026Convergence Analysis of Tsetlin Machines under Noise-Free and Noisy Training Conditions: from $2$ Bits to $k$ Bits
- ICLR 2026Convergence of Regret Matching in Potential Games and Constrained Optimization
- ICLR 2026Convergent Differential Privacy Analysis for General Federated Learning
- ICLR 2026COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representations
- ICLR 2026Cross-Domain Lossy Compression via Rate- and Classification-Constrained Optimal Transport
- ICLR 2026CSRv2: Unlocking Ultra-Sparse Embeddings
- ICLR 2026CUPID: A Plug-in Framework for Joint Aleatoric and Epistemic Uncertainty Estimation with a Single Model
- ICLR 2026Curse of Slicing: Why Sliced Mutual Information is a Deceptive Measure of Statistical Dependence
- ICLR 2026DAVE: A VLM Vision Encoder for Document Understanding and Web Agents
- ICLR 2026Debiased and Denoised Projection Learning for Incomplete Multi-view Clustering
- ICLR 2026Debugging Concept Bottleneck Models through Removal and Retraining
- ICLR 2026Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning
- ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
- ICLR 2026Decoupling Positional and Symbolic Attention in Transformers
- ICLR 2026Decoupling the Class Label and the Target Concept in Machine Unlearning
- ICLR 2026DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification
- ICLR 2026Difference Predictive Coding for Training Spiking Neural Networks
- ICLR 2026Differentiable Lifting for Topological Neural Networks
- ICLR 2026Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
- ICLR 2026DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities
- ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
- ICLR 2026Disentangled representation learning through unsupervised symmetry group discovery
- ICLR 2026Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
- ICLR 2026DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
- ICLR 2026Diverse Dictionary Learning
- ICLR 2026Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Models
- ICLR 2026Dual Perspectives on Non-Contrastive Self-Supervised Learning
- ICLR 2026Dual-Branch Representations with Dynamic Gated Fusion and Triple-Granularity Alignment for Deep Multi-View Clustering
- ICLR 2026Einstein Fields: A Neural Perspective To Computational General Relativity
- ICLR 2026Error Feedback for Muon and Friends
- ICLR 2026Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
- ICLR 2026Explainable $ K $-means Neural Networks for Multi-view Clustering
- ICLR 2026Fairness via Independence: A General Regularization Framework for Machine Learning
- ICLR 2026FeDaL: Federated Dataset Learning for General Time Series Foundation Models
- ICLR 2026Federated Graph-Level Clustering Network with Dual Knowledge Separation
- ICLR 2026FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments
- ICLR 2026Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning
- ICLR 2026FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
- ICLR 2026Fore-Mamba3D: Mamba-based Foreground-Enhanced Encoding for 3D Object Detection
- ICLR 2026From Parameters to Behaviors: Unsupervised Compression of the Policy Space
- ICLR 2026From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
- ICLR 2026From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning
- ICLR 2026FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing
- ICLR 2026Gauge Flow Matching: Efficient Constrained Generative Modeling over General Convex Set and Beyond
- ICLR 2026General Exploratory Bonus for Optimistic Exploration in RLHF
- ICLR 2026General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
- ICLR 2026Generalization Below the Edge of Stability: The Role of Data Geometry
- ICLR 2026Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · unsupervised and semisupervised learning在 ICML 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "gml-unsupervised-and-semisupervised-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- 共 2,683 篇,按年份分别是 2023 年 649 篇、2024 年 553 篇、2025 年 682 篇、2026 年 799 篇。
- NeurIPS 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- NeurIPS 2026 有 194 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 203 篇。
- ICLR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- ICLR 2026 有 187 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 174 篇。
- ICML 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- ICML 2026 有 348 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 239 篇。
- CVPR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- CVPR 2026 有 70 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 66 篇。
- 哪个会议的通用机器学习 · unsupervised and semisupervised learning论文最多?
- ICML,2023–2026 年共 859 篇。